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Relationship between Musculoskeletal Discomfort and

Workstyle Risk Factors among Information

Technology Professionals in India

Sharan D1, Ajeesh PS1

1RECOUP Neuromusculoskeletal Rehabilitation Centre, Bangalore, India

Introduction

Prevalence of work-related musculoskeletaldisorders (WRMSD) is common inInformation Technology (IT) professionalsthroughout the world.

Introduction

Based on psychosocial, physiological, andbehavioral response that occurs in anindividual during high work demands,Feuerstein and colleagues defined theconcept of “Workstyle”1.

Workstyle has been identified as a mediatingfactor in the relation between job demandsand musculoskeletal discomfort of the upperextremity2.

(Feuerstein, 1996)1, (Feuerstein, Carosella, Burrell, Marshall, & Decaro, 1997; Gerr et al., 2002)2

Objective

This study was aimed to find out therelationship of work related musculoskeletaldisorders and work-style risk factors amongIT professionals.

Review of literature

Approximately 76% of computer professionals from India reported symptoms of musculoskeletal discomfort in various epidemiological studies including pain in neck, back, wrists and shoulder.

(Bakhtiar & Vijaya, 2003; Sharma, Khera, & Khandekar, 2006; Talwar, Kapoor, Puri, Bansal, & Singh, 2009).

Risk factors

Various factors such as poor office ergonomics, working long hours and static postures were identified as risk factors leading to the pain and discomfort.

(Bakhtiar & Vijaya, 2003; Sharma, et al., 2006; Talwar, et al., 2009)

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Psychosocial risk factors

National Institute of Occupational Health and Safety (NIOSH) has identified five psychosocial factors related to musculoskeletal disorders, i.e., job satisfaction, intensified workload, monotonous work, job control, and social support.

(Bernard, 1997)=

Psychosocial risk factors

Recently, strong associations between boredom, workload, and social support to musculoskeletal discomfort in computer professionals from India were reported.

(Bhanderi, Choudhary, Parmar, & Doshi, 2007)

Risk factors

Although WRMSDs have been shown to result primarily from biomechanical stressors such as forceful exertions, static postures and repetition1.

there is an increasing evidence that psychosocial work factors may trigger or worsen WRMSDs2.

Methodology

Participants: The data presented in thisstudy was extracted from various ITprofessionals who were a part of Ergonomicworkplace evaluation organized by theircompany.

N = 4512

Procedure

The methods was as follows:

1. Demographics (age, gender etc.)

2. Workstation information

3. Working posture information (i.e., headand neck in line with torso, forearm, wristand hand in line)

4. Perceived pain and discomfort

5. Workstyle questionnaire developed byFeuerstein

Procedure

Based on technology used, participants were divided into desktop or laptop users.

Duration of computer use per day was also recorded.

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Outcome Measures

The adverse workstyle in the participantswas assessed using the score from the 32item workstyle questionnaire1.

The questionnaire consists of 8 subscales(i.e. working through pain, social reactivity,limited workplace support, breaks, deadlinesand pressure, self-imposed workload, mood,and autonomic)

(Feuerstein & Nicholas, 2006)

Data Analysis

Workstyle scores were individually calculated using formula mentioned in literature

Correlation coefficient computed using inferential statistics

Statistical analyses were conducted using the SPSS 17.0 package with a significance level set at p <0.05 for all tests.

Demography

Average age 29.9 ± 10.2 years

Gender 76 % males and 24% females

Demography

Category Percentage (%)

Duration of computer use per day

< 4 hrs. 1

4 - 6 hrs. 9

7 -9 hrs. 46

> 9 hrs. 45

Technology used

Desktop 75

Laptop 25

Results

The short form workstyle questionnairescore analysis indicated 22% of overallparticipants were at a high risk (score≥ 28) of adverse workstyle.

63% of participants reported pain anddiscomfort during or shortly after theyfinish work on the computer.

34% of participants experiencednumbness/tingling sensation in theirfingers after working on the computer

Results

Loss of strength in hands was reported by 33% of participants

13% of participants indicated a loss in productivity due to the symptoms of pain and discomfort

Less than 1% of participants indicated that days were taken off work due to the pain symptoms.

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Correlation Analyses

Correlation analyses revealed that pain wassignificantly correlated with the total:

1. Workstyle score (r = 0.39, p = 0.05),

2. Daily computer usage (r = 0.46, p = 0.004)

3. Micro break (r = 0.87, p = 0.001)

4. Productivity (r = 0.95, p = 0.001)

Discussion

Participants with a high pain and workstyle score would indicate “days off work” due to the symptoms, the results indicated low incidence.

Discussion

Certain limitations exist in the present study.

Firstly, the data was randomly selected from previous database and therefore there was no control over the experimental design.

Secondly, factors such as work injury claims, existing medical condition/trauma, and ergonomic risk factors (posture at work, use of mouse trays etc.) were not available from the previous dataset.

Conclusion

This study show significant associations between psychosocial factors such as workstyle and the presence of musculoskeletal pain.

Based on the findings of this study, it is recommended that psychosocial factors should be incorporated in designing intervention strategies to reduce work-related musculoskeletal symptoms.

Thank you

info@recoup.in

academic@recoup.in

www.recoup.in

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